Polyurethane composite spray forming online detection and supplementary spraying method

Abstract

The application discloses a polyurethane composite material spray forming online detection and supplementary spraying method and relates to the technical field of composite material spray forming. The method comprises the following steps: S1, providing a composite fiber layer which is alternately laminated by glass fiber cloth and glass fiber chopped felt; S2, spraying polyurethane resin on the surface of the composite fiber layer; S3, within a first preset time after S2 is completed, acquiring an infrared thermal imaging feature map by an infrared detection device, comparing the feature map with a standard infiltration feature database, identifying an infiltration defect grade, performing point supplementary spraying by a mechanical hand and performing re-inspection; S4, transferring the qualified spray mixture to a forming mold; and S5, closing the mold, heating, pressurizing and curing and forming. The gel time of the polyurethane resin is T_s, the transfer time is T_t, T_t is less than 80% of T_s, and the first preset time is 20% to 40% of T_t. The application realizes closed-loop quality control of the spray forming process by online detection of the resin infiltration state and automatic supplementary spraying, and the forming quality and production efficiency of the battery pack upper cover are improved.

Description

Technical Field

[0001] This invention relates to the technical field of composite material spraying and molding, specifically to an online monitoring and re-spraying process for the wetting quality of polyurethane composite material spraying, and particularly to an online detection and re-spraying method for the spraying and molding of a new energy battery pack cover. Background Technology

[0002] With the rapid development of the new energy vehicle industry, battery pack covers, as key structural components of battery systems, not only need to provide mechanical protection and sealing, but also need to meet various performance requirements such as lightweighting, flame retardancy, and insulation. Polyurethane composite materials, due to their excellent mechanical properties, chemical corrosion resistance, and good process adaptability, have broad application prospects in the field of battery pack covers.

[0003] Currently, existing polyurethane composite material molding processes mainly have the following shortcomings:

[0004] Firstly, Chinese patent CN118977483A discloses "a glass fiber reinforced polyurethane sprayed cover plate and its preparation process," which involves laying glass fiber layers on both sides of a paper core, spraying a polyurethane foaming agent onto the surface, and then molding it into a foam. However, this process uses a traditional spraying method, relying on manual visual inspection or experience to judge the resin's wetting effect on the glass fiber after spraying. This makes it impossible to accurately locate and quantitatively replenish unevenly wetting areas, easily leading to substandard mechanical properties of the product due to poor local wetting, resulting in a high scrap rate.

[0005] Secondly, Chinese patent CN117681468A discloses a "Resin Flow Monitoring System for High-Temperature RTM Process," which uses electrodes and a voltage acquisition device inside the mold to monitor the position of the resin flow front and the degree of curing in the high-temperature RTM process in real time. However, this patent's monitoring system requires embedding electrodes inside the mold, resulting in a complex system structure, high cost, and the inability to detect the uniformity of resin wetting in the fiber layer thickness direction. It also lacks effective online detection and closed-loop feedback methods for the common problem of uneven surface wetting in spraying processes.

[0006] Third, Chinese patent CN119571242B discloses a "visual-guided laser shock thermal imaging composite coating spraying method," which uses a high-speed infrared thermal imager to collect the temperature field distribution on the coating surface in real time, identifies defects, and then adjusts the spraying process parameters in real time through a self-feedback PID control system. Although this patent achieves closed-loop control of infrared detection and spraying parameter feedback adjustment, its detection object is crack defects on the coating surface, and its detection mechanism is based on the transient thermal response generated by laser shock, which is different from the infrared thermal imaging detection mechanism based on the exothermic reaction of polyurethane resin wetting in this application; moreover, its feedback method is to adjust the spraying process parameters in real time, rather than to perform fixed-point re-spraying and re-inspection of the already sprayed area.

[0007] In summary, existing polyurethane composite material molding processes have significant shortcomings in online detection and closed-loop feedback control of resin impregnation quality. In particular, there is a lack of an intelligent molding process that can detect the impregnation status in real time during the spraying process, automatically identify impregnation defects, and perform targeted re-spraying. This makes it difficult to meet the requirements of high pass rate and consistency for battery pack covers. Summary of the Invention

[0008] The purpose of this invention is to provide an online detection and re-spraying method for polyurethane composite material spraying molding, so as to solve the problems mentioned in the background art.

[0009] To achieve the above objectives, the present invention provides an online detection and re-spraying method for polyurethane composite material spraying molding, which adopts the following technical solution:

[0010] A method for online detection and re-spraying of polyurethane composite material spraying molding includes the following steps:

[0011] S1: Provides a composite fiber layer consisting of alternating layers of fiberglass cloth and chopped strand mat;

[0012] S2: Polyurethane resin is sprayed onto the surface of the composite fiber layer to form a spray mixture;

[0013] S3: Within a first preset time after step S2 is completed, an infrared thermal imaging feature map of the surface of the sprayed mixture is obtained by an infrared detection device, compared with a preset standard wetting feature database, the wetting defect area and defect level are identified, the re-spraying parameters are automatically matched according to the defect level, the robot arm performs fixed-point re-spraying, and the re-inspection is carried out after re-spraying.

[0014] S4: Transfer the spray mixture that has passed the S3 test to the molding die;

[0015] S5: Molding, heating, and pressurizing are applied for curing and molding;

[0016] Wherein, the gel time of the polyurethane resin is T_s, the transfer time from the completion of S2 to the start of mold closing in S5 is T_t, T_t < T_s × 80%, and the first preset time is 20% to 40% of T_t.

[0017] By adopting the above technical solution, after S2 is completed, within the first preset time, the infrared detection device acquires the thermal imaging feature map of the sprayed mixture surface, compares it with the standard wetting feature database, identifies the wetting defect area and defect level, automatically matches the re-spraying parameters according to the defect level, and performs fixed-point re-spraying by the robot, and forms a closed-loop control by re-inspection after re-spraying; at the same time, the polyurethane resin gel time T_s and the transfer time T_t are limited to satisfy T_t < T_s × 80%, and the first preset time is set to 20% to 40% of T_t, ensuring that the spraying exothermic development, detection, re-spraying, transfer into the mold, and mold closing and curing are completed sequentially before the resin gels, taking into account both the stability of thermal imaging development and the wetting fluidity after re-spraying.

[0018] Preferably, in step S3, the wetting defects are classified into minor defects and major defects according to the distance value of the thermal characteristic parameter; minor defects are repaired with low pressure and low amount of spraying, while major defects are repaired with standard pressure, large amount of spraying, and multiple sprayings using a grid or spiral trajectory.

[0019] By adopting the above technical solution, wetting defects are divided into two levels: mild and severe, and different repair spraying strategies are matched for each level: mild defects are repaired with a low flow rate in a single spray to avoid local excessive resin and uneven thickness; severe defects are repaired with multiple cross-spraying, which improves the uniformity of repair spraying by stacking multiple small amounts, ensuring that severely under-wetting areas are fully wetted, while reducing resin waste caused by over-spraying.

[0020] Preferably, the fiberglass cloth is modified by soaking in a silane coupling agent hydrolysate before being laid up.

[0021] By adopting the above technical solution, the surface of the glass fiber cloth is chemically modified by the silane coupling agent hydrolysate, organic functional groups are introduced into the glass fiber surface, the interfacial bonding force between the glass fiber and the polyurethane resin is enhanced, thereby improving the interlaminar shear strength and mechanical properties of the composite material.

[0022] Preferably, the upper and lower surfaces of the composite fiber layer are both made of fiberglass cloth, and the basis weight of the fiberglass cloth is 2 to 3 times that of chopped strand mat.

[0023] By adopting the above technical solution, the upper and lower surface layers are made of fiberglass cloth, which provides good surface quality and protective performance. The middle layer is made of fiberglass chopped strand mat, which provides good resin impregnation channels and thickness filling effect. The basis weight of fiberglass cloth is 2 to 3 times that of chopped strand mat, which ensures that the upper and lower surface layers have sufficient mechanical strength and impact resistance, while avoiding warping and deformation caused by excessive differences between the inner and outer layers.

[0024] Preferably, the molding die cavity in step S4 is provided with a retractable embedded part positioning mechanism, which is used to position the metal insert in the cavity before mold closing, and retracts during mold closing to cover and fix the insert in the product.

[0025] By adopting the above technical solution, the retractable embedded part positioning mechanism fixes the metal insert in the preset position in the cavity before the sprayed mixture is put into the mold, ensuring that the insert does not shift during the molding process and guaranteeing the positional accuracy of the insert; during the mold closing process, the positioning mechanism retracts to the surface of the mold cavity, allowing the flowing resin material to wrap the insert. After curing, the insert is firmly embedded in the battery pack cover, eliminating the need for subsequent secondary processing or drilling, thus simplifying the production process.

[0026] Preferably, during the pressure holding process in step S5, the curing status is monitored in real time by an in-mold sensor and the pressure holding time is dynamically adjusted.

[0027] By adopting the above technical solution, sensors are embedded in the mold to monitor the changes in temperature, pressure or ultrasonic signals during the curing process in real time. The holding time is dynamically adjusted according to the resin curing state reflected by these signals, avoiding the problems of insufficient or excessive holding pressure caused by the curing speed fluctuation in the traditional fixed holding time process, thus improving the stability and consistency of molding quality.

[0028] Preferably, the composite fiber layer includes an interface toughening layer.

[0029] By adopting the above technical solution, the interface toughening layer forms a flexible transition layer between the fiberglass cloth and the chopped strand mat, which effectively alleviates the stress concentration between layers and improves the impact resistance and interlaminar fracture toughness of the composite material.

[0030] This invention achieves closed-loop quality control of the spraying and molding process by detecting the resin wetting state online through infrared thermal imaging and automatically matching the respraying parameters. The quantitative relationship between gel time and transfer time ensures the controllability of the process window. The overall process realizes full-process intelligence and automation from layup, spraying, detection, respraying, molding to curing, which significantly improves the molding quality and production efficiency of polyurethane composite materials. Attached Figure Description

[0031] Figure 1 This is a schematic flowchart of the online detection and re-spraying method for polyurethane composite material spraying molding according to the present invention.

[0032] Figure 2 This is a schematic diagram of the stacked structure of the composite fiber layer of the present invention.

[0033] Figure 3 This is a schematic diagram of the structure of the molding mold cavity and the pre-embedded part positioning mechanism of the present invention.

[0034] Figure 4 This is a schematic diagram of the principle of the infrared detection and fixed-point spraying closed-loop control system of the present invention.

[0035] Figure 5 This is a monitoring diagram of the curing state of the in-mold sensor of this invention. Detailed Implementation

[0036] The following is in conjunction with the appendix Figure 1-5 The present invention will be described in further detail below.

[0037] Example 1

[0038] like Figures 1 to 5 As shown in the figure, this embodiment provides an online detection and re-spraying method for polyurethane composite material spraying molding, including the following steps.

[0039] S1: The composite fiber layer is composed of alternating layers of fiberglass cloth and chopped strand mat. For example... Figure 2 As shown, the top and bottom layers of the composite fiber layer are both made of fiberglass cloth, and the middle layer consists of alternating layers of fiberglass cloth and chopped fiberglass mat. Specifically, in this embodiment, a three-layer structure is adopted: the top and bottom layers are fiberglass cloth, and the middle layer is chopped fiberglass mat. The basis weight of the fiberglass cloth is 800 g / m², and the basis weight of the chopped fiberglass mat is 350 g / m², with the basis weight of the fiberglass cloth being approximately 2.3 times that of the chopped fiberglass mat.

[0040] Before being laid up, the fiberglass cloth is modified by soaking in a silane coupling agent hydrolysate. The specific process is as follows: the fiberglass cloth is immersed in a 1.5% silane coupling agent hydrolysate for 30 minutes, and then dried at 100°C for 20 minutes.

[0041] S2: Polyurethane resin is uniformly sprayed onto the surface of the composite fiber layer using a spraying device at a temperature of 23℃~25℃, allowing the polyurethane resin to fully impregnate the composite fiber layer and form a sprayed mixture. During spraying, the temperature of the polyurethane resin is 24℃, and the ambient humidity is controlled at 40%~60%. The gel time T_s of the polyurethane resin is determined by the resin formulation; in this embodiment, T_s is approximately 120 seconds.

[0042] S3: As Figure 4 As shown, within a first preset time after S2 is completed, an infrared thermal imaging feature map of the sprayed mixture surface is acquired by an infrared detection device. The first preset time is 20% to 40% of T_t, where T_t is the transfer time from the completion of S2 to the start of mold closing in S5, and T_t satisfies T_t < T_s × 80%. In this embodiment, T_t is designed to be 80 seconds, T_s is 120 seconds, and T_t / T_s ≈ 66.7% < 80%, which meets the requirements. The first preset time is taken as 30% of T_t, i.e., 24 seconds.

[0043] The infrared detection device includes an infrared thermal imager and an image processing unit. The infrared thermal imager has a resolution of 640×480 pixels and a frame rate of 30Hz. It is installed above the detection station downstream of the spraying station to perform non-contact scanning imaging of the sprayed mixture surface. Because the polyurethane resin undergoes an exothermic reaction during impregnation, a temperature difference exists between well-impregnated and poorly impregnated areas. The infrared thermal imager can capture the thermal imaging features formed by this temperature difference.

[0044] The infrared thermal imaging feature map is compared with a pre-set standard wetting feature database. The standard wetting feature database consists of infrared thermal imaging feature vectors of multiple qualified samples, constructed through offline acquisition. Specifically, the image processing unit extracts the thermal feature parameter vector of the area to be tested and compares it with the Mahalanobis distance (or Euclidean distance) between the feature vectors of qualified templates in the database. When the calculated distance exceeds a pre-set first threshold, it is determined to be an wetting anomaly, and the wetting defect level is determined according to the distance: a distance exceeding the first threshold but not exceeding the second threshold is a minor defect, and a distance exceeding the second threshold is a severe defect.

[0045] The system automatically matches respraying parameters based on the wetting defect level. A calibration plate is used to perform hand-eye calibration of the infrared thermal imager and the robotic arm, establishing a mapping relationship between image pixel coordinates and robotic arm motion coordinates. The robotic arm then performs targeted respraying on areas with uneven wetting. Minor defects correspond to a single low-flow respray, with the respray volume being 40% of the theoretical requirement for that area, and the spraying pressure being 65% of the normal pressure. Severe defects correspond to multiple cross-spraying operations, with the respray volume being 90% of the theoretical requirement for that area, the spraying pressure being the standard pressure, and a grid-like trajectory for uniform coverage.

[0046] After the fixed-point re-spraying is completed, the infrared detection device re-inspects the re-sprayed area. If the re-inspection result still exceeds the threshold, the re-spraying and re-inspection steps are repeated until the preset maximum number of re-spraying times is reached (3 times in this embodiment). If the standard is still not met after reaching the maximum number of re-spraying times, the sprayed mixture is marked as a defective product and stops from entering the subsequent process.

[0047] S4: Transfer the qualified spray coating mixture into the cavity of the molding die. For example... Figure 3 As shown, the molding die cavity is equipped with a retractable embedded part positioning mechanism, which is used to position the metal insert in a predetermined position within the cavity before the transfer of the sprayed mixture. The metal insert is a threaded insert, which is pre-fixed by the positioning pin of the embedded part positioning mechanism. During the mold closing process, the embedded part positioning mechanism retracts to the surface of the mold cavity, allowing the flowing resin material to encapsulate the metal insert. After curing, the insert is firmly encapsulated and fixed inside the battery pack cover.

[0048] S5: Mold closing. The sprayed mixture is heated and pressurized to cure and solidify in the molding mold. The mold temperature is controlled at 120℃~150℃, the molding pressure is 5MPa~10MPa, and the holding time is dynamically adjusted according to the curing state.

[0049] like Figure 5 As shown, during the pressure holding process, sensors embedded in the molding die monitor the curing state parameters of the sprayed mixture in real time. The sensors include a temperature sensor and a pressure sensor. The temperature sensor detects the peak value of the resin curing exothermic curve, and the pressure sensor detects the position of the resin flow front. When the temperature sensor detects that the curing exothermic curve has reached its peak and begins to decline, it indicates that the resin matrix has essentially cured; when the pressure sensor detects that the pressure inside the cavity is stabilizing, it indicates that the resin flow has essentially stopped. Based on these curing state parameters, the control system dynamically adjusts the pressure holding time. When all curing state parameters meet the preset curing completion conditions, the control system issues a command to end the pressure holding and open the mold to remove the molded part. In this embodiment, the typical pressure holding time is 3 to 8 minutes, with the specific duration dynamically determined by the real-time monitoring data from the sensors.

[0050] The standard wetting feature database is built offline during the process development phase:

[0051] The specific method involves preparing a batch of qualified spray coating samples (no fewer than 50 pieces) under the same process conditions. Within the first preset time window after S2, infrared thermal images of the surface of each sample are acquired using an infrared detection device. After image preprocessing, including effective region selection, size normalization and formatting, and centering, the acquired thermal images are continuously acquired at a frame rate of 30Hz within the first preset time window. The heating rate is calculated by dividing the temperature difference of the same pixel area in two adjacent frames by the frame interval. The other four parameters are the calculated values ​​from the last frame. Thermal feature parameter vectors for each sample are extracted from the preprocessed thermal images. These vectors include at least five dimensions: mean temperature, temperature variance, temperature gradient, heating rate, and temperature extreme value difference. The feature vectors of all qualified samples are aggregated to form a standard wetting feature database. Simultaneously, the mean vector μ and covariance matrix C of all feature vectors in the database are calculated. In actual production, the database is updated and maintained periodically or irregularly according to process adjustments.

[0052] Calculation of Mahalanobis distance and Euclidean distance:

[0053] Let the thermal characteristic parameter vector of the region to be tested be V_test=[v1,v2,v3,v4,v5]^T, the mean vector of the standard database be μ=[μ1,μ2,μ3,μ4,μ5]^T, and the covariance matrix be Σ.

[0054] The Euclidean distance is calculated as follows: D_E=√[Σ(v_j-μ_j)²] (j=1 to 5), which is the square root of the sum of the squares of the differences between the corresponding components of the vector to be measured and the mean vector.

[0055] The formula for calculating Mahalanobis distance is: D_M = √[(V_test - μ)^T·C -1 ·(V_test-μ)], where C -1 This is the inverse of the covariance matrix C. Unlike Euclidean distance, Mahalanobis distance eliminates the correlation between feature dimensions through the covariance matrix and normalizes different units, resulting in higher detection accuracy.

[0056] During actual testing, the Mahalanobis or Euclidean distance between the thermal characteristic parameter vector of the test area and the standard database is calculated. When the distance value exceeds the first threshold, it is considered an infiltration anomaly; when it exceeds the second threshold (second threshold > first threshold), it is considered a severe defect; and when it exceeds the first threshold but not the second threshold, it is considered a minor defect. The first and second thresholds are determined through offline experiments. Specifically, known qualified and unqualified samples are collected, their characteristic distance values ​​are calculated, and the optimal discrimination threshold is selected through ROC curve analysis.

[0057] Example 2

[0058] like Figure 2 As shown, the difference between this embodiment and Embodiment 1 is that the composite fiber layer adopts a different layered structure.

[0059] Specifically, the composite fiber layer consists of five layers, from bottom to top: fiberglass cloth, chopped fiberglass mat, fiberglass cloth, chopped fiberglass mat, and fiberglass cloth. The top and bottom layers are both fiberglass cloth, while the middle layer consists of alternating layers of fiberglass cloth and chopped fiberglass mat. An interface toughening layer, a thermoplastic polyurethane (TPU) film with a thickness of 0.05 mm to 0.15 mm, is provided between adjacent layers of fiberglass cloth and chopped fiberglass mat. The TPU film melts during the hot-pressing process, forming a flexible transition layer between the fiberglass cloth and chopped fiberglass mat, effectively alleviating interlayer stress concentration.

[0060] In addition, an interface toughening layer is provided at a predetermined interlayer position of the composite fiber layer. In this embodiment, a mica paper layer is provided below the intermediate fiberglass cloth as an interface toughening layer, and the thickness of the mica paper layer is 0.1 mm to 0.3 mm, providing high-temperature resistant insulation protection for the battery pack cover.

[0061] The remaining steps and parameters are the same as in Example 1, and will not be repeated here.

[0062] Example 3

[0063] like Figure 4As shown, the difference between this embodiment and embodiment 1 is that the infrared detection and supplementary spray control in S3 use different parameter configurations.

[0064] Specifically, an infrared thermal imager is mounted above the spraying station at a 45° angle to scan and image the surface of the sprayed mixture. The standard wetting feature database is constructed using principal component analysis (PCA) to reduce the dimensionality of the infrared thermal imaging feature map, extracting the top 10 principal components as feature vectors. The similarity between the feature vector of the area to be tested and the feature vector of the qualified template is calculated using Euclidean distance.

[0065] Regarding the respraying parameters, for minor defects, the respray amount is 30% of the theoretical requirement for that area, and the spraying pressure is 60% of the normal pressure; for severe defects, the respray amount is 80% of the theoretical requirement for that area, and the spraying pressure is 100% of the standard pressure. The respraying trajectory adopts a spiral trajectory. The maximum number of resprays is set to 2.

[0066] Regarding the process time parameters, the gel time T_s of the polyurethane resin is 150 seconds, the transfer time T_t is 100 seconds, and T_t / T_s ≈ 66.7% < 80%, which meets the requirements. The first preset time is 20% of T_t, i.e., 20 seconds.

[0067] The remaining steps and parameters are the same as in Example 1, and will not be repeated here.

[0068] Example 4

[0069] like Figure 5 As shown, the difference between this embodiment and embodiment 1 is that the configuration of the in-mold sensor in S5 is different.

[0070] Specifically, the sensors embedded in the molding die include a temperature sensor and an ultrasonic sensor. The temperature sensor monitors the resin curing exothermic curve in real time, while the ultrasonic sensor emits ultrasonic waves into the sprayed mixture and receives the echo signals. The changes in resin viscosity are reflected by the attenuation and propagation speed of the echo signals. When the resin viscosity increases to a preset threshold, it indicates that the curing has reached the predetermined degree.

[0071] The control system determines the curing completion status based on the peak value of the curing exothermic curve detected by the temperature sensor and the resin viscosity change detected by the ultrasonic sensor. When the peak value of the curing exothermic curve has passed and the resin viscosity reaches the preset demolding threshold, curing is considered complete, the pressure holding is ended, and the mold is opened.

[0072] The remaining steps and parameters are the same as in Example 1, and will not be repeated here.

[0073] Example 5

[0074] like Figure 2As shown, the difference between this embodiment and Embodiment 1 is that the composite fiber layer is provided with an interface toughening layer, and the interface toughening layer uses a different combination of materials.

[0075] In this embodiment, the composite fiber layer adopts a seven-layer structure: fiberglass cloth, chopped strand mat, fiberglass cloth, chopped strand mat, fiberglass cloth, chopped strand mat, and fiberglass cloth. An expanded graphite layer is placed as an interface toughening layer in the middle layer (between the fourth layer of chopped strand mat and the fifth layer of fiberglass cloth), with a thickness of 0.2mm to 0.5mm. The expanded graphite layer rapidly expands at high temperatures to form a carbonaceous heat insulation layer, effectively preventing the propagation of flames and heat into the battery pack, significantly improving the flame-retardant performance of the battery pack cover.

[0076] Meanwhile, an interface toughening layer is provided between the upper and lower surface fiberglass cloth and the adjacent chopped strand mat. The interface toughening layer is an elastomer microsphere coating. The elastomer microspheres are uniformly coated on the surface of the fiberglass cloth by spraying. The microsphere particle size is 10μm to 50μm and the coating amount is 20g / m² to 50g / m².

[0077] As the thickness of the fiber layer in the seven-layer structure increases, the resin impregnation time is correspondingly extended. Therefore, in this embodiment, T_s is adjusted to 180 seconds, and T_t is designed to be 120 seconds (T_t / T_s≈66.7%<80%). The first preset time is 25% of T_t, i.e., 30 seconds, to ensure that the infrared detection has sufficient development stability and the impregnation fluidity of the subsequent respraying operation.

[0078] The remaining steps and parameters are the same as in Example 1, and will not be repeated here.

[0079] Comparative Example 1: The detection window is 10% of T_t.

[0080] The remaining conditions were exactly the same as in Example 1, except that the first preset time in S3 was set to 10% of T_t. The results showed that because the polyurethane resin had just been sprayed, the exothermic reaction had not yet fully reached the surface, the signal-to-noise ratio of the infrared thermal imaging feature map was extremely low, and the calculated thermal feature parameter distance value fluctuated by more than ±35%. This led to a large number of qualified areas being misjudged as wetting defects, resulting in frequent false triggering of the respraying system. Ultimately, multiple local resin deposits appeared on the product surface, and the thickness uniformity did not meet the standards.

[0081] Comparative Example 2: The detection window is 50% of T_t.

[0082] The remaining conditions were exactly the same as in Example 1, except that the first preset time in S3 was set to 50% of T_t. The results showed that although the infrared feature map was clear, the gel time T_s was close to the critical point when the respray was completed. The resprayed resin was transferred into the mold before it could fully wet the fiber layer. After curing, obvious resin and fiber delamination occurred in the resprayed area, and the interlayer shear strength decreased by about 28% compared with Example 1.

[0083] Comparative experiments in Examples 1 and 2 show that: if the first preset time of S3 is less than 20% of T_t, the development stability and signal-to-noise ratio of infrared thermal imaging cannot meet the accuracy requirements of online detection, leading to serious system misjudgments and production line disruptions; if the first preset time is greater than 40% of T_t, the time margin between the re-spraying process and the subsequent transfer into the mold process is insufficient, and the re-sprayed resin cannot achieve effective wetting before gelation, ultimately causing internal defects in the cured product. Therefore, limiting the first preset time of S3 to the range of 20% to 40% of T_t achieves the optimal balance between thermal imaging development stability and the wetting fluidity after re-spraying.

[0084] In summary, this invention utilizes infrared thermal imaging to perform online detection of the wetting state of polyurethane resin after spraying. By comparing the infrared thermal imaging feature map with a standard wetting feature database, it automatically identifies the wetting defect level and matches the re-spraying parameters. A robotic arm enables closed-loop control for targeted re-spraying and re-inspection. The process window is controlled by the quantitative relationship between gel time T_s and transfer time T_t, ensuring all operations are completed before resin gelation. A retractable pre-embedded part positioning mechanism enables one-time molding and embedding of metal inserts. Sensors within the mold monitor the curing state in real time and dynamically adjust the holding pressure time. Interfacial toughening layers impart multiple functional properties to the composite material. The overall process achieves intelligent and automated control throughout the entire process, from layup, spraying, detection, re-spraying, mold placement, molding to curing, significantly improving the molding quality and production efficiency of the battery pack cover.

[0085] The above are all preferred embodiments of the present invention and are not intended to limit the scope of protection of this application. Therefore, all equivalent changes made in accordance with the structure, shape and principle of this application should be covered within the scope of protection of this application.

Claims

1. A method for online detection and re-spraying of polyurethane composite material spraying molding, characterized in that: Includes the following steps: S1: Provides a composite fiber layer consisting of alternating layers of fiberglass cloth and chopped strand mat; S2: Polyurethane resin is sprayed onto the surface of the composite fiber layer to form a spray mixture; S3: Within a first preset time after step S2 is completed, an infrared thermal imaging feature map of the surface of the sprayed mixture is obtained by an infrared detection device, compared with a preset standard wetting feature database, the wetting defect area and defect level are identified, the re-spraying parameters are automatically matched according to the defect level, the robot arm performs fixed-point re-spraying, and the re-inspection is carried out after re-spraying. S4: Transfer the spray mixture that has passed the S3 test to the molding die; S5: Molding, heating, and pressurizing are applied for curing and molding; Wherein, the gel time of the polyurethane resin is T_s, the transfer time from the completion of S2 to the start of mold closing in S5 is T_t, T_t < T_s × 80%, and the first preset time is 20% to 40% of T_t.

2. The method for online detection and re-spraying of polyurethane composite material spraying as described in claim 1, characterized in that: In S3, wetting defects are classified into mild defects and severe defects according to the distance value of thermal characteristic parameters; mild defects are repaired with low pressure and low amount of spraying, while severe defects are repaired with standard pressure, large amount of spraying, and multiple sprayings using grid or spiral trajectory.

3. The online detection and re-spraying method for polyurethane composite material spraying molding according to claim 1, characterized in that: The fiberglass cloth is modified by soaking in a silane coupling agent hydrolysate before being laid up.

4. The online detection and re-spraying method for polyurethane composite material spraying molding according to claim 1, characterized in that: The upper and lower surfaces of the composite fiber layer are both made of fiberglass cloth, and the basis weight of the fiberglass cloth is 2 to 3 times that of chopped strand mat.

5. The online detection and re-spraying method for polyurethane composite material spraying molding according to claim 1, characterized in that: In step S4, the molding mold cavity is provided with a retractable embedded part positioning mechanism, which is used to position the metal insert in the cavity before mold closing and retracts during mold closing to cover and fix the insert in the product.

6. The method for online detection and re-spraying of polyurethane composite material spraying as described in claim 1, characterized in that: During step S5, the curing status is monitored in real time by an in-mold sensor, and the holding time is dynamically adjusted.

7. The method for online detection and re-spraying of polyurethane composite material spraying as described in claim 1, characterized in that: The composite fiber layer includes an interface toughening layer.

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